Abstract
Grid computing is a hot issue of high performance computing. In order to improve the overall performance and computational efficiency of the grid system, the common resource allocation and scheduling algorithms are compared and analyzed. Combining the advantages and disadvantages of various algorithms, the grid scheduling framework is first constructed. Then the optimized grid resource allocation and task scheduling strategy are proposed. The scheduling strategy fully considers the QoS requirements of the computing task and the dynamic change characteristics of the grid, and the average residence time of each computing task. Finally, the simulation experiment is used to verify the propose the performance of the scheduling strategy.
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This work was supported by the project of Nature Scientific Foundation of Heilongjiang Province (F2016038).
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Guo, W., Liu, F. (2020). Optimized Grid Resource Allocation and Task Scheduling Strategy. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019. ATCI 2019. Advances in Intelligent Systems and Computing, vol 1017. Springer, Cham. https://doi.org/10.1007/978-3-030-25128-4_19
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DOI: https://doi.org/10.1007/978-3-030-25128-4_19
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